Jan Peters

Jan Peters is a full professor (W3) for Intelligent Autonomous Systems at the Computer Science Department of the Technische Universitaet Darmstadt and at the same time an adjunct senior research scientist at the Max-Planck Institute for Intelligent Systems, where he heads the interdepartmental Robot Learning Group between the departments of Bernhard Schoelkopf and Stefan Schaal.

Previously, Jan Peters has been a full-time Senior Research Scientist and Robot Learning Group Leader in the department of Bernhard Schoelkopf the Max-Planck Institute of Biological Cybernetics since 2007. Even earlier, he completed a Ph.D. at the Department of Computer Science at the University of Southern California (USC) in Los Angeles. There, Jan has been working with Stefan Schaal, Sethu Vijayakumar (now at U. Edinburgh, UK), and Firdaus Udwadia (Department of Mechanical Engineering). Chris Atkeson (Robotics Institute at CMU) and Gaurav Sukhatme also guided him to his thesis. In 2011, Jan Peters' PhD Thesis received the Dick Volz Best 2007 US PhD Thesis Runner Up Award based on thesis quality and thesis impact. Jan remains affiliated with the CLMC Lab as an invited researcher.

Before joining USC's Computer Science Ph.D. program and the CLMC Lab in Fall 2001, Jan Peters graduated from the University of Hagen in 2000 with a Diplom-Informatiker (German M.Sc. in Computer Science, focus on artificial intelligence) and from Munich University of Technology in 2001 with a Diplom-Ingenieur in Electrical Engineering (German M.Eng. in Electrical Engineering, majoring in automation & control). In 2000-2001, he spent two semesters as visiting student at National University of Singapore. In 2002, he completed a M.Sc. in Computer Science (focus on Machine Learning) and, in 2005, a M.Sc. in Mechanical Engineering (Major: Nonlinear Dynamics & Control) both from USC. Jan Peters has been a visiting research student at the Department of Robotics at the German Aerospace Research Center in Germany, at Siemens Advanced Engineering in Singapore and at the Department of Humanoid Robotics and Computational Neuroscience at the Advanded Telecommunication Research (ATR) Center in Japan. Please see his curriculum vitae for more biographical information.

As Jan Peters' research lies at the intersection between two fields, i.e., machine learning and robotics, he has always keen to bring members of both fields together. To do so, he has organized three NIPS workshops (Towards a New Reinforcement Learning!, Robotics Challenges for Machine Learning and Probabilistic Approaches for Robotics and Control), three R:SS Workshops (Learning for Locomotion, Bridging the gap between high-level discrete representations and low-level continuous behaviors and Towards Closing the Loop: Active Learning for Robotics), two IROS workshops (From motor to interaction learning in robots and Robotics Challenges for Machine Learning II), one ICRA workshop (Approaches to Sensorimotor Learning on Humanoid Robots) and one ECAI workshop (The 6th International Cognitive Robotics Workshop). His Co-Organizers included Pieter Abeel (U. Berkeley), Drew Bagnell (CMU), Andreas Krause (CalTech), Dana Kulic (U. Waterloo), Ruben Martinez-Cantin (IST Lisbon/U.Zaragoza), Jun Morimoto (ATR), Nick Roy (MIT), Stefan Schaal (USC), Olivier Sigaud (U.Paris 6), Russ Tedrake (MIT), Marc Toussaint (TU Berlin), Sethu Vijayakumar (U.Edingburgh), Gerhard Lakemeyer (RWTH Aachen, Germany), Yves Lespérance (York University, Canada), Fiora Pirri (University of Rome "La Sapienza", Italy), Ales Ude (Josef Stefan Institute, Slovenia), Tamim Asfour (U.Karlsruhe).

In 2008, Nick Roy (MIT), Russ Tedrake (MIT), Jun Morimoto (ATR) and Jan Peters founded the IEEE Robotics and Automation Society's Technical Committee on Robot Learning which won the 2010 Most Active Technical Committee Award. In 2009, Jan Peters and Andrew Y. Ng (Stanford) have edited a Special Issue on Robot Learning in the Autonomous Robots journal. Jan Peters has been an Area Chair at Robotics: Science & Systems (R:SS), at the European Conference on Machine Learning (ECML), at the International Conference on Neural Networks (ICANN), at International Conference on Artificial Intelligence & Statistics (AIStats) and at Advances in Neural Information Processing Systems (NIPS). Since November 2011, Jan Peters is an Associate Editor for the IEEE Transactions on Robotics.

Jan Peters can be found on Google Citations and DBLP.

Research Interests: Motor Control and Learning, Robotics, Machine Learning, Biomimetic Systems
Biographical Information: Please see his curriculum vitae.
Publications: For the complete list of his publication, see here.

Key References

  1. Peters, J.; Muelling, K.; Altun, Y. (2010). Relative Entropy Policy Search, Proceedings of the Twenty-Fourth National Conference on Artificial Intelligence (AAAI), Physically Grounded AI Track  download [PDF]
  2. Peters, J.;Schaal, S. (2008). Reinforcement learning of motor skills with policy gradients, Neural Networks, 21, 4, pp.682-97  download [PDF]
  3. Peters, J.;Schaal, S. (2008). Natural actor critic, Neurocomputing, 71, 7-9, pp.1180-1190  download [PDF]
  4. Peters, J.;Schaal, S. (2007). Reinforcement learning by reward-weighted regression for operational space control, Proceedings of the International Conference on Machine Learning (ICML2007)  download [PDF]
    with an applied version in Peters, J.;Schaal, S. (2008). Learning to control in operational space, International Journal of Robotics Research, 27, pp.197-212  download [PDF]
  5. Kober, J.; Peters, J. (2009). Policy Search for Motor Primitives in Robotics, Advances in Neural Information Processing Systems 22 (NIPS 2008), Cambridge, MA: MIT Press  download [PDF]
    with a longer version in Kober, J.; Peters, J. (2011). Policy Search for Motor Primitives in Robotics, Machine Learning, 84, 1-2, pp.171-203  download [PDF]
  6. Peters, J.;Mistry, M.;Udwadia, F. E.;Nakanishi, J.;Schaal, S. (2008). A unifying framework for robot control with redundant DOFs, Autonomous Robots, 24, 1, pp.1-12  download [PDF]
  7. Nakanishi, J.;Cory, R.;Mistry, M.;Peters, J.;Schaal, S. (2008). Operational space control: A theoretical and emprical comparison, International Journal of Robotics Research, 27, 6, pp.737-757  download [PDF]
  8. Nguyen-Tuong, D.; Seeger, M.; Peters, J. (2009). Local Gaussian Process Regression for Real Time Online Model Learning and Control, Advances in Neural Information Processing Systems 22 (NIPS 2008), Cambridge, MA: MIT Press  download [PDF]
    with a longer version in Nguyen-Tuong, D.; Seeger, M.; Peters, J. (2009). Model Learning with Local Gaussian Process Regression, Advanced Robotics, 23, 15, pp.2015-2034  download [PDF]
  9. Kober, J.; Oztop, E.; Peters, J. (2011). Reinforcement Learning to adjust Robot Movements to New Situations, Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Best Paper Track  download [PDF]
  10. Muelling, K.; Kober, J.; Peters, J. (2011). A Biomimetic Approach to Robot Table Tennis, Adaptive Behavior Journal, 19, 5  download [PDF]

Contact Information

Mail: Jan Peters, TU Darmstadt, FB Informatik, FG IAS, Hochschulstr. 10, 64289 Darmstadt
Office: Room E314, Robert-Piloty-Gebaeude S2|02
work +49-6151-167351
fax +49-6151-167374

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